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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Study of argon expulsion from the post-disruption runaway electron plateau following low-Z massive gas injection in DIII-D

Herein, a 1D radial diffusion model is developed to study the observed rapid expulsion of argon from the runaway electron plateau in the DIII-D tokamak following secondary massive low-Z (D 2 or He) gas injection. The expulsion of argon is found to be caused by further cooling of the background plasma due to the added neutrals, accompanied by recombination of argon ions and greatly increased outward radial transport rate of argon (now dominantly in neutral form) out of the runaway electron beam. After argon expulsion, power loss out of the runaway electron plateau is found to be dominated by neutral transport to the wall (rather than by radiation); this result resolves the power balance discrepancy highlighted in previous work on argon expulsion out of the runaway electron plateau.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Faster network disruption from layered oscillatory dynamics

Nonlinear complex network-coupled systems typically have multiple stable equilibrium states. Following perturbations or due to ambient noise, the system is pushed away from its initial equilibrium, and, depending on the direction and the amplitude of the excursion, it might undergo a transition to another equilibrium. It was recently demonstrated [M. Tyloo, J. Phys. Complex. 3 03LT01 (2022)] that layered complex networks may exhibit amplified fluctuations. Here, I investigate how noise with system-specific correlations impacts the first escape time of nonlinearly coupled oscillators. Interestingly, I show that, not only the strong amplification of the fluctuations is a threat to the good functioning of the network but also the spatial and temporal correlations of the noise along the lowest-lying eigenmodes of the Laplacian matrix. Finally, I analyze first escape times on synthetic networks and compare noise originating from layered dynamics to uncorrelated noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Disruption of a key ligand-H-bond network drives dissociative properties in vamorolone for Duchenne muscular dystrophy treatment

Duchenne muscular dystrophy is a genetic disorder that shows chronic and progressive damage to skeletal and cardiac muscle leading to premature death. Antiinflammatory corticosteroids targeting the glucocorticoid receptor (GR) are the current standard of care but drive adverse side effects such as deleterious bone loss. Through subtle modification to a steroidal backbone, a recently developed drug, vamorolone, appears to preserve beneficial efficacy but with significantly reduced side effects. We use combined structural, biophysical, and biochemical approaches to show that loss of a receptor-ligand hydrogen bond drives these remarkable therapeutic effects. Moreover, vamorolone uniformly weakens coactivator associations but not corepressor associations, implicating partial agonism as the main driver of its dissociative properties. Additionally, we identify a critical and evolutionarily conserved intramolecular network connecting the ligand to the coregulator binding surface. Interruption of this allosteric network by vamorolone selectively reduces GR-driven transactivation while leaving transrepression intact. Our results establish a mechanistic understanding of how vamorolone reduces side effects, guiding the future design of partial agonists as selective GR modulators with an improved therapeutic index.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Myosin dilated cardiomyopathy mutation S532P disrupts actomyosin interactions, leading to altered muscle kinetics, reduced locomotion, and cardiac dilation in Drosophila

Dilated cardiomyopathy (DCM), a life-threatening disease characterized by pathological heart enlargement, can be caused by myosin mutations that reduce contractile function. To better define the mechanistic basis of this disease, we employed the powerful genetic and integrative approaches available in Drosophila melanogaster. To this end, we generated and analyzed the first fly model of human myosin–induced DCM. The model reproduces the S532P human β-cardiac myosin heavy chain DCM mutation, which is located within an actin-binding region of the motor domain. In concordance with the mutation’s location at the actomyosin interface, steady-state ATPase and muscle mechanics experiments revealed that the S532P mutation reduces the rates of actin-dependent ATPase activity and actin binding and increases the rate of actin detachment. The depressed function of this myosin form reduces the number of cross-bridges during active wing beating, the power output of indirect flight muscles, and flight ability. Further, S532P mutant hearts exhibit cardiac dilation that is mutant gene dose–dependent. Our study shows that Drosophila can faithfully model various aspects of human DCM phenotypes and suggests that impaired actomyosin interactions in S532P myosin induce contractile deficits that trigger the disease.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Disruption of p -coumaroyl-CoA:monolignol transferases in rice drastically alters lignin composition

Grasses are abundant feedstocks that can supply lignocellulosic biomass for production of cell-wall-derived chemicals. In grass cell walls, lignin is acylated with p-coumarate. These p-coumarate decorations arise from the incorporation of monolignol p-coumarate conjugates during lignification. A previous biochemical study identified a rice (Oryza sativa) BAHD acyltransferase (AT) with p-coumaroyl-CoA:monolignol transferase (PMT) activity in vitro. In this study, we determined that that enzyme, which we name OsPMT1 (also known as OsAT4), and the closely related OsPMT2 (OsAT3) harbor similar catalytic activity toward monolignols. We generated rice mutants deficient in either or both OsPMT1 and OsPMT2 by CRISPR/Cas9-mediated mutagenesis and subjected the mutants’ cell walls to analysis using chemical and nuclear magnetic resonance methods. Our results demonstrated that OsPMT1 and OsPMT2 both function in lignin p-coumaroylation in the major vegetative tissues of rice. Notably, lignin-bound p-coumarate units were undetectable in the ospmt1 ospmt2-2 double-knockout mutant. Further, in-depth structural analysis of purified lignins from the ospmt1 ospmt2-2 mutant compared with control lignins from wild-type rice revealed stark changes in polymer structures, including alterations in syringyl/guaiacyl aromatic unit ratios and inter-monomeric linkage patterns, and increased molecular weights. Furthermore, our results provide insights into lignin polymerization in grasses that will be useful for the optimization of bioengineering approaches for the effective use of biomass in biorefineries.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

4'-Deoxypyridoxine disrupts vitamin B 6 homeostasis in Escherichia coli K12 through combined inhibition of cumulative B 6 uptake and PLP-dependent enzyme activity

Pyridoxal 5'-phosphate (PLP) is the active form of vitamin B 6 and a cofactor for many essential metabolic processes such as amino acid biosynthesis and one carbon metabolism. 4’-deoxypyridoxine (4dPN) is a long known B 6 antimetabolite but its mechanism of action was not totally clear. By exploring different conditions in which PLP metabolism is affected in the model organism Escherichia coli K12, we showed that 4dPN cannot be used as a source of vitamin B 6 as previously claimed and that it is toxic in several conditions where vitamin B 6 homeostasis is affected, such as in a B 6 auxotroph or in a mutant lacking the recently discovered PLP homeostasis gene, yggS . In addition, we found that 4dPN sensitivity is likely the result of multiple modes of toxicity, including inhibition of PLP-dependent enzyme activity by 4’-deoxypyridoxine phosphate (4dPNP) and inhibition of cumulative pyridoxine (PN) uptake. These toxicities are largely dependent on the phosphorylation of 4dPN by pyridoxal kinase (PdxK).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms

There has been an increase in extreme weather events, posing a threat to power grid systems, potentially influenced by factors such as population growth, changes in ecosystems, land cover, and land use in the service area, as well as the growth of certain vegetation types. This research seeks to develop a predictive model to mitigate potential damages caused by future winter storms. This research utilizes the Light Gradient Boosting Machine (LightGBM), incorporating the number of power outages experienced at the county level, geographic details, weather information, and lagged outage and lagged weather data. The developed models were broadly divided into two groups, with six models in each group - one group without optimization and another with optimization, totaling 12 trained models. For model optimization, Bayesian optimization was employed using Root Mean Squared Error (RMSE) as the objective function. In results, when comparing Group 2 (the optimized group) with Group 1 (the non-optimized group), it was found that optimization did not always lead to a reduction in RMSE and Mean Absolute Error (MAE). However, in terms of Mean Directional Accuracy (MDA), while all results in Group 1 were below the baseline accuracy of 0.33, all results in Group 2 exceeded 0.33, with some cases showing an increase of more than three times the baseline. The results indicated that, in the optimized model group, Population and Pressure were the most influential factors when using current weather data and geographical information. When using lagged data, lagged recorded outages and lagged Pressure emerged as the most significant factors. Among the 12 developed models, the L-1-2-O model showed the lowest RMSE and MAE, as well as the highest accuracy, with values of 390.62 households and 168.13 households, respectively. To normalize the RMSE and MAE values, each metric was divided by the average number of households among the counties in Texas. For the L-1-2-O model, the scaled RMSE was 0.88% and the scaled MAE was 0.38%. In terms of MDA, which indicates the accuracy of the prediction direction, the L-1-O model achieved the highest score of 0.41. Although this study focused on Texas, which suffered the greatest impact from the winter storms in 2021, with additional validation, the methodology used in this research could be applied to other regions.

Lee, Jangjae [Texas A & M Univ., College Station, ↗